Concentration and Moment Inequalities for Polynomials of Independent Random Variables

Details Concentration and Moment Inequalities for Polynomials of Independent Random Variables Concentration and Moment Inequalities for Polynomials of Independent Random Variables

2011-04-26

arxiv.org/abs/1104.4997v2

Mathematics

Probability

46 pages

Scientific paper

In this work we design a general method for proving moment inequalities for polynomials of independent random variables. Our method works for a wide range of random variables including Gaussian, Boolean, exponential, Poisson and many others. We apply our method to derive general concentration inequalities for polynomials of independent random variables. We show that our method implies concentration inequalities for some previously open problems, e.g. permanent of a random symmetric matrices. We show that our concentration inequality is stronger than the well-known concentration inequality due to Kim and Vu. The main advantage of our method in comparison with the existing ones is a wide range of random variables we can handle and bounds for previously intractable regimes of high degree polynomials and small expectations. On the negative side we show that even for boolean random variables each term in our concentration inequality is tight.

Affiliated with

Also associated with

No associations

Rating

Concentration and Moment Inequalities for Polynomials of Independent Random Variables does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Concentration and Moment Inequalities for Polynomials of Independent Random Variables, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Concentration and Moment Inequalities for Polynomials of Independent Random Variables will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-297118